Modeling and controlling the Caltech Ducted Fan Vehicle

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Modeling and controlling the Caltech Ducted Fan
Vehicle
Steve Neuendorffer EE290N Final Presentation
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How do we get to an implementation?
Abstract, high-level system model
Detailed low-level system implementation
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Some options

• Don't build a high-level model Implement the
  system by hand.
• Build a high-level model, but throw it away when
  implementation starts.
• Build a high-level model, and validate
  implementation against it.
• Build a low-level model, and generate an
  implementation from it.
• Build a high-level model, refine it gradually
  into more detailed models that are more suitable
  for automatic code generation.

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An example of heterogenous refinement

• Drive the ducted fan vehicle to a desired point.
• Continuous time vehicle and controller.
• A zero-delay discrete-time controller.
• A one-step delay discrete-time controller.
• An arbitrary delay discrete-time controller.
• A more sophisticated modal controller.
• A model for automatic system implementation.

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1 Vehicle/Controller model
(X,Y) Position, and direction of the vehicle
Total forward thrust, and differential torque
applied by the fans.
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1 Continuous Vehicle model
Specified as a differential equation, as in
Simulink.
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1 Continuous controller model
A modified proportional controller
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2 Vehicle model withDiscrete-time interface
Zero-order hold models the Digital -gt Analog
conversion.
The analog position of the vehicle is
periodically sampled approximately every second.
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2 Discrete Vehicle controller
Heterogenous system modeling
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3 Discrete Vehicle controller with one-sample
delay
SampleDelay added to model computation time of
controller
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4 Discrete Vehicle controller with arbitrary
delay
TimedDelay actor in Discrete Event domain models
arbitrary delay.
More Heterogeneity
SDF control law
CT vehicle model
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5 A modal controller
Yet More Heterogeneity
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Breathe and watch the demo
A comparison of the modal controller versus the
simple proportional controller.
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Target specifics
(X,Y) Position, and direction of the vehicle come
from video localization system.
Control values are sent to motor controller by
serial port.
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6 A controller, with refined communication.
Suitable for code generation
One of the previous (possibly heterogenous)contro
l laws
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Conclusion
I used Ptolemy II to model a physical control
system at an high-level of granularity using an
abstract model of computation. The high level
model was manually refined through several
intermediate steps to the point where the model
was detailed enough to automatically generate the
controller code.